{"pageNumber":"606","pageRowStart":"15125","pageSize":"25","recordCount":184689,"records":[{"id":70215138,"text":"70215138 - 2020 - Methods to quality assure, plot, summarize, interpolate, and extend groundwater-level information—Examples for the Mississippi River Valley alluvial aquifer","interactions":[],"lastModifiedDate":"2020-10-08T12:49:28.043168","indexId":"70215138","displayToPublicDate":"2020-07-03T07:42:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7147,"text":"Journal of Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Methods to quality assure, plot, summarize, interpolate, and extend groundwater-level information—Examples for the Mississippi River Valley alluvial aquifer","docAbstract":"

Large-scale computational investigations of groundwater levels are proposed to accelerate science delivery through a workflow spanning database assembly, statistics, and information synthesis and packaging. A water-availability study of the Mississippi River alluvial plain, and particularly the Mississippi River Valley alluvial aquifer (MRVA), is ongoing. Software (visGWDBmrva) has been released as part of the study that demonstrates groundwater informatics for the aquifer. Considerable water-level data collected by multiple agencies over a seven-state area exist (18,903 wells; 287,272 measurements [April 22, 2019]). Data and metadata quality assurance methods, basic statistics, hydrograph visualization, outlier identification, hypothesis testing, and time-series modeling are described. Two approaches (generalized additive models [GAMs] and support vector machines [SVMs]) are used for data interpolation and extension to monthly water-level estimates. Numerical congruence between GAM and SVM estimates will be useful to limit inclusion of monthly estimates from subsequent science activities.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2020.104758","usgsCitation":"Asquith, W.H., Seanor, R.C., McGuire, V.L., and Kress, W., 2020, Methods to quality assure, plot, summarize, interpolate, and extend groundwater-level information—Examples for the Mississippi River Valley alluvial aquifer: Journal of Environmental Modelling and Software, v. 134, 104758, 19 p., https://doi.org/10.1016/j.envsoft.2020.104758.","productDescription":"104758, 19 p.","ipdsId":"IP-101493","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":456132,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2020.104758","text":"Publisher Index Page"},{"id":436897,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PR7V63","text":"USGS data release","linkHelpText":"Quality Assurance of Water Level Records from Wells in the Mississippi River Valley Alluvial Aquifer in Missouri from the Missouri Department of Natural Resource's Well Information Management System (WIMS)"},{"id":379218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.3623046875,\n 42.908160071960566\n ],\n [\n -92.3291015625,\n 39.87601941962116\n ],\n [\n -90.703125,\n 36.63316209558658\n ],\n [\n -91.845703125,\n 34.77771580360469\n ],\n [\n -93.251953125,\n 31.27855085894653\n ],\n [\n -91.0107421875,\n 27.994401411046173\n ],\n [\n -88.59375,\n 28.9600886880068\n ],\n [\n -89.6923828125,\n 30.486550842588485\n ],\n [\n -90.00000000000001,\n 32.39851580247402\n ],\n [\n -88.330078125,\n 36.45663601159623\n ],\n [\n -89.0771484375,\n 38.134556577054134\n ],\n [\n -90.1318359375,\n 39.94343646197423\n ],\n [\n -89.736328125,\n 41.934976500546604\n ],\n [\n -90.17578125,\n 42.74701217318067\n ],\n [\n -91.3623046875,\n 42.908160071960566\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"134","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":800979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seanor, Ronald C. 0000-0001-5735-5580","orcid":"https://orcid.org/0000-0001-5735-5580","contributorId":218443,"corporation":false,"usgs":true,"family":"Seanor","given":"Ronald","email":"","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":800980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, Virginia L. 0000-0002-3962-4158 vlmcguir@usgs.gov","orcid":"https://orcid.org/0000-0002-3962-4158","contributorId":404,"corporation":false,"usgs":true,"family":"McGuire","given":"Virginia","email":"vlmcguir@usgs.gov","middleInitial":"L.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":800981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kress, Wade 0000-0002-6833-028X","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":203539,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":800982,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216415,"text":"70216415 - 2020 - msocc: Fit and analyse computationally efficient multi‐scale occupancy models in R","interactions":[],"lastModifiedDate":"2020-11-17T23:48:25.126332","indexId":"70216415","displayToPublicDate":"2020-07-02T17:45:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"msocc: Fit and analyse computationally efficient multi‐scale occupancy models in R","docAbstract":"
  1. Environmental DNA (eDNA) sampling is a promising tool for the detection of rare and cryptic taxa, such as aquatic pathogens, parasites and invasive species. Environmental DNA sampling workflows commonly rely on multi‐stage hierarchical sampling designs that induce complicated dependencies within the data. This complex dependence structure can be intuitively modelled with Bayesian multi‐scale occupancy models. However, current software for such models are computationally demanding, impeding their use.
  2. We present an r package, msocc, that implements a data augmentation strategy to fit fully Bayesian, computationally efficient multi‐scale occupancy models. The msocc package allows users to fit multi‐scale occupancy models, to estimate and visualize posterior summaries of site, sample and replicate‐level occupancy, and to compare different models using Bayesian information criterion. Additionally, we provide a supplemental web application that allows users to investigate study design for multi‐scale occupancy models and acts as a graphical user interface to the msocc package.
  3. The utility of the msocc package is illustrated on a published dataset and the functions in msocc are compared to the primary Bayesian toolkit for multi‐scale occupancy modelling, eDNAoccupancy, using various computational benchmarks. These benchmarks indicate that msocc is capable of fitting models 50 times faster than eDNAoccupancy.
  4. We hope that access to software that efficiently fits, analyses and conducts study design investigations for multi‐scale occupancy models facilitates their implementation by the research and wildlife management communities.
","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.13442","usgsCitation":"Stratton, C., Sepulveda, A.J., and Hoegh, A.B., 2020, msocc: Fit and analyse computationally efficient multi‐scale occupancy models in R: Methods in Ecology and Evolution, v. 11, no. 9, p. 1113-1120, https://doi.org/10.1111/2041-210X.13442.","productDescription":"8 p.","startPage":"1113","endPage":"1120","ipdsId":"IP-116614","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":456135,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13442","text":"Publisher Index Page"},{"id":380563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Stratton, Christian","contributorId":217711,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":804952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":804953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoegh, Andrew B.","contributorId":166684,"corporation":false,"usgs":false,"family":"Hoegh","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":804954,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208486,"text":"ofr20201013 - 2020 - Biological assessment of a proposed vegetation management program to benefit tribes in eastern Oklahoma","interactions":[],"lastModifiedDate":"2021-03-08T23:10:07.993397","indexId":"ofr20201013","displayToPublicDate":"2020-07-02T16:30:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1013","displayTitle":"Biological Assessment of a Proposed Vegetation Management Program to Benefit Tribes in Eastern Oklahoma","title":"Biological assessment of a proposed vegetation management program to benefit tribes in eastern Oklahoma","docAbstract":"

Tribal communities may benefit from land management activities that enhance their use of resources on tribal lands. The Bureau of Indian Affairs is implementing a 5-year vegetation management program to provide support for projects that develop and use natural and cultural resources and improve opportunities for agricultural activities to benefit 20 Indian Tribes and Nations in the Eastern Oklahoma Region of the Bureau of Indian Affairs. The bureau is working with individual Tribes to identify project objectives and design treatments, which include prescribed burning, timber removal, thinning, and reduction of hazardous fuels. The total action area for the vegetation management program is estimated to be 236,575 acres, representing approximately 1 percent of the region.

A biological assessment was prepared, in cooperation with the bureau and U.S. Fish and Wildlife Service, to evaluate the potential effects of the proposed vegetation management program on 22 federally threatened, endangered, and candidate species that may occur within the Eastern Oklahoma Region. The species evaluated included one plant, two insects, one reptile, five fresh-water mussels, four fishes, five birds, and four bats. Because the proposed treatments will be largely restricted to terrestrial systems, it is expected that there will be no adverse effects on the 15 species associated with aquatic habitats, provided that best management practices are followed. The proposed treatments may affect but are unlikely to adversely affect six of the primarily terrestrial species (the Papaipema eryngii [rattlesnake master borer], Picoides borealis [red-cockaded woodpecker], Myotis grisescens [gray bat], Myotis sodalis [Indiana bat], Myotis septentrionalis [northern long-eared bat], and Corynorhinus townsendii ingens [Ozark big-eared bat]), provided that best management practices are followed, including avoidance of critical habitat features.

The only species likely to be adversely affected by the proposed treatments is Nicrophorus americanus (American burying beetle) as a consequence of short-term disturbances to soils and vegetation. Most adverse effects of the treatments (such as soil compaction and decreased cover in the forest understory) are expected to be short term (habitat will recover or be restored within 5 years of treatments). Less than 1 percent of the action area is expected to result in long-term adverse effects to the American burying beetle as a result of permanent cover changes that persist for more than 5 years. It is expected that the primary treatments will be largely beneficial to the American burying beetle population in the region by reducing the risk of high-severity fires and expansion of invasive woody shrubs, such as Juniperus virginiana (eastern redcedar) within potential beetle habitat and the surrounding landscape. Overall, the proposed management program is expected to provide long-term benefits to American burying beetle habitat across 91 percent of the action area.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20201013","collaboration":"Prepared in cooperation with the Bureau of Indian Affairs and U.S. Fish and Wildlife Service","usgsCitation":"Harms, B.R., Bencin, H.L., and Carr, N.B., 2020, Biological assessment of a proposed vegetation management program to benefit Tribes in eastern Oklahoma: U.S. Geological Survey Open-File Report 2020–1013, 49 p., \nhttps://doi.org/10.3133/ofr20201013.","productDescription":"Report: vi, 49 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-111270","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":376079,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95LDGHX","text":"USGS data release","linkHelpText":"Estimated habitat suitability for the American burying beetle using land cover classes in the Southern Plains (ver. 1.1, June 2020)"},{"id":376078,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1013/ofr20201013.pdf","text":"Report","size":"2.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1013"},{"id":376077,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1013/coverthb.jpg"},{"id":384231,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1013/versionHist.txt","text":"version history","size":"9.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2020-1013 version history"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.6142578125,\n 36.99377838872517\n ],\n [\n -96.844482421875,\n 36.98500309285596\n ],\n [\n -96.92138671875,\n 36.61552763134925\n ],\n [\n -97.00927734375,\n 36.421282443649496\n ],\n [\n -96.064453125,\n 36.13787471840729\n ],\n [\n -96.52587890625,\n 35.951329861522666\n ],\n [\n -96.88842773437499,\n 35.7019167328534\n ],\n [\n -97.14111328125,\n 34.939985151560435\n ],\n [\n -97.789306640625,\n 35.27253175660236\n ],\n [\n -98.031005859375,\n 35.28150065789119\n ],\n [\n -98.0859375,\n 34.161818161230386\n ],\n [\n -97.9541015625,\n 33.86129311351553\n ],\n [\n -97.591552734375,\n 34.016241889667015\n ],\n [\n -97.305908203125,\n 33.78827853625996\n ],\n [\n -97.108154296875,\n 33.897777013859475\n ],\n [\n -96.99829101562499,\n 33.73347670599252\n ],\n [\n -96.45996093749999,\n 33.715201644740844\n ],\n [\n -95.712890625,\n 33.87041555094183\n ],\n [\n -95.284423828125,\n 33.86129311351553\n ],\n [\n -95.11962890625,\n 33.93424531117312\n ],\n [\n -94.449462890625,\n 33.61461929233378\n ],\n [\n -94.449462890625,\n 35.38904996691167\n ],\n [\n -94.6142578125,\n 36.99377838872517\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118

","tableOfContents":"","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2020-07-02","revisedDate":"2021-03-05","noUsgsAuthors":false,"publicationDate":"2020-07-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Harms, Benjamin R. 0000-0001-7570-6962","orcid":"https://orcid.org/0000-0001-7570-6962","contributorId":222413,"corporation":false,"usgs":true,"family":"Harms","given":"Benjamin","email":"","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":792020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bencin, Heidi L. 0000-0002-0879-5392","orcid":"https://orcid.org/0000-0002-0879-5392","contributorId":222412,"corporation":false,"usgs":true,"family":"Bencin","given":"Heidi","email":"","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":792021,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carr, Natasha B. 0000-0002-4842-0632 carrn@usgs.gov","orcid":"https://orcid.org/0000-0002-4842-0632","contributorId":1918,"corporation":false,"usgs":true,"family":"Carr","given":"Natasha","email":"carrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":792022,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210915,"text":"70210915 - 2020 - In situ observations of wave transformation and infragravity bore development across reef flats of varying geomorphology","interactions":[],"lastModifiedDate":"2020-07-03T01:50:37.470357","indexId":"70210915","displayToPublicDate":"2020-07-02T15:27:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"displayTitle":"In situ observations of wave transformation and infragravity bore development across reef flats of varying geomorphology","title":"In situ observations of wave transformation and infragravity bore development across reef flats of varying geomorphology","docAbstract":"The character and energetics of infragravity (IG, 25 s < period < 250 s) and very-low frequency (VLF, period > 250 s) waves over coral reef flats can enhance shoreline erosion or accretion, and also govern extreme shoreline events such as runup, overwash, and flooding on coral reef-lined coasts. Here we use in situ wave measurements collected along cross-reef transects at 7 sites on Pacific islands with varying reef geomorphologies to examine under what conditions IG waves occur and what factors enhance their irregularity. In general, a greater fraction of total wave energy was transferred to the IG band on reefs with steeper fore reef slopes and shallower reef flats. The IG wave amplitudes scaled with increasing water levels, but it was primarily at lower water levels when these waves became pitched onshore (negatively asymmetrical) and peaked (positively skewed). However, our results also highlight the importance of reef-flat width and slope as important morphological controls on IG waves, as the most asymmetric, bore-like, IG waves occurred on the wider reef flats, and the most skewed IG waves at the site with the steepest reef-flat. On the wider reef flats, IG wave-wave capture was observed during periods of large offshore wave forcing and enhanced VLF wave energy. Because similar IG wave motions over plane beaches enhance sea-swell (SS, period < 25 s) bore-merging in the surf zone, we posit that VLF waves over reef flats may facilitate IG bore merging, and this may lead to larger, more pitched-onshore bores at the shoreline. In addition, greater IG wave heights appear to support the transmission of larger secondary short-period waves over the reef flat, independent of overall water levels. As irregular IG waves may be strong drivers of cross-reef sediment transport as well as runup, understanding the conditions and reef geomorphologies that lead to low-frequency, energetic bores on reef flats is critical to forecasting how coral reef-lined coasts will respond to sea-level rise and climate change.","language":"English","publisher":"Frontiers Media S.A.","doi":"10.3389/fmars.2020.00351","usgsCitation":"Cheriton, O.M., Storlazzi, C.D., and Rosenberger, K.J., 2020, In situ observations of wave transformation and infragravity bore development across reef flats of varying geomorphology: Frontiers in Marine Science, v. 7, 351, 16 p., https://doi.org/10.3389/fmars.2020.00351.","productDescription":"351, 16 p.","ipdsId":"IP-116934","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":456137,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2020.00351","text":"Publisher Index Page"},{"id":376110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Republic of the Marshall Islands, United States","state":"Hawaii","otherGeospatial":"Kwajalein, Maui, Molokai, Roi-Namur","volume":"7","noUsgsAuthors":false,"publicationDate":"2020-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":792123,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":792124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":792125,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210917,"text":"70210917 - 2020 - Selective sediment transport during Hurricane Sandy on Fire Island (New York, USA): Inferences from heavy-mineral assemblages","interactions":[],"lastModifiedDate":"2020-07-03T01:53:37.74296","indexId":"70210917","displayToPublicDate":"2020-07-02T15:15:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2451,"text":"Journal of Sedimentary Research","onlineIssn":"1938-3681","printIssn":"1527-1404","active":true,"publicationSubtype":{"id":10}},"title":"Selective sediment transport during Hurricane Sandy on Fire Island (New York, USA): Inferences from heavy-mineral assemblages","docAbstract":"In October 2012, Hurricane Sandy caused severe erosion on beaches and dunes of Fire Island (New York, USA). Major shoreline changes occurred with erosional dominance in the upper shoreline and aggradation in the lowermost section of the beach due to the deposition of eroded upper beach and dune sediment. Sand laminations with a high concentration of heavy minerals (“black sand laminations”) were observed in three excavated trenches located on a washover terrace and fan on the east side of Fire Island. The mineralogical composition of these laminations reveals the presence of high quantities of magnetite, ilmenite (as opaque minerals), and garnet (as main translucent mineral). These heavy mineral enriched laminations were formed as waves eroded and transported sand from the primary dune and smaller relict dunes under specific hydrodynamic conditions that promoted grain sorting according to differences in size and specific gravity. Based on the concentrations of certain heavy minerals, the threshold for primarily density-driven sorting probably lies between the specific gravity of a less dense mineral (ilmenite, 4.7) and Garnet almandine (4.3), the most common transparent heavy mineral. The number of laminations and concentrations of heavy minerals vary between trenches on the overwash terrace and appear to be controlled by their distance from sediment sources. The trench with a greatest number of laminations and higher heavy mineral concentrations is located furthest from the main dune but is just 10 m inland of a relict dune that acts as the primary source of sediment of the washover deposit in this trench. A conceptual model for heavy mineral layer deposition is presented based on geomorphological and sedimentological evidences allowing the definition of a density threshold.","language":"English","publisher":"SEPM","doi":"10.2110/jsr.2020.12","usgsCitation":"Cascalho, J., Costa, P., Gelfenbaum, G.R., La Selle, S., and Jaffe, B.E., 2020, Selective sediment transport during Hurricane Sandy on Fire Island (New York, USA): Inferences from heavy-mineral assemblages: Journal of Sedimentary Research, v. 90, no. 3, p. 269-285, https://doi.org/10.2110/jsr.2020.12.","productDescription":"17 p.","startPage":"269","endPage":"285","ipdsId":"IP-099491","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":376109,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.96295166015625,\n 40.68896903762434\n ],\n [\n -72.8668212890625,\n 40.68896903762434\n ],\n [\n -72.8668212890625,\n 40.73997376331186\n ],\n [\n -72.96295166015625,\n 40.73997376331186\n ],\n [\n -72.96295166015625,\n 40.68896903762434\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"90","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Cascalho, Joao","contributorId":228808,"corporation":false,"usgs":false,"family":"Cascalho","given":"Joao","email":"","affiliations":[{"id":41512,"text":"Instituto D. Luiz and Departamento de Geologia, Faculdade de Ciências da Universidade de Lisboa","active":true,"usgs":false}],"preferred":false,"id":792126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costa, Pedro","contributorId":228809,"corporation":false,"usgs":false,"family":"Costa","given":"Pedro","affiliations":[{"id":41513,"text":"1Instituto D. Luiz and Departamento de Geologia, Faculdade de Ciências da Universidade de Lisboa","active":true,"usgs":false}],"preferred":false,"id":792127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gelfenbaum, Guy R. 0000-0003-1291-6107 ggelfenbaum@usgs.gov","orcid":"https://orcid.org/0000-0003-1291-6107","contributorId":742,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","email":"ggelfenbaum@usgs.gov","middleInitial":"R.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":792128,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Selle, SeanPaul 0000-0002-4500-7885 slaselle@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-7885","contributorId":181565,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul","email":"slaselle@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":792129,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":792130,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210908,"text":"70210908 - 2020 - Space use and relative habitat selection for immature green turtles within a Caribbean marine protected area","interactions":[],"lastModifiedDate":"2020-07-03T02:06:58.740547","indexId":"70210908","displayToPublicDate":"2020-07-02T13:22:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Space use and relative habitat selection for immature green turtles within a Caribbean marine protected area","docAbstract":"Background\nA better understanding of sea turtle spatial ecology is critical for the continued conservation of imperiled sea turtles and their habitats. For resource managers to develop the most effective conservation strategies, it is especially important to examine how turtles use and select for habitats within their developmental foraging grounds. Here, we examine the space use and relative habitat selection of immature green turtles (Chelonia mydas) using acoustic telemetry within the marine protected area, Buck Island Reef National Monument (BIRNM), St. Croix, United States Virgin Islands.\n\nResults\nSpace use by turtles was concentrated on the southern side of Buck Island, but also extended to the northeast and northwest areas of the island, as indicated by minimum convex polygons (MCPs) and 99%, 95%, and 50% kernel density estimations (KDEs). On average space use for all categories was<3 km2 with mean KDE area overlap ranging from 41.9 to 67.7%. Cumulative monthly MCPs and their proportions to full MCPs began to stabilize 3 to 6 detection months after release, respectively. Resource selection functions (RSFs) were implemented using a generalized linear mixed effects model with turtle ID as the random effect. After model selection, the accuracy of the top model was 77.3% and showed relative habitat selection values were highest at shallow depths, for areas in close proximity to seagrass, and in reef zones for both day and night, and within lagoon zones at night. The top model was also extended to predict across BIRNM at both day and night.\n\nConclusion\nMore traditional acoustic telemetry analyses in combination with RSFs provide novel insights into animal space use and relative resource selection. Here, we demonstrated immature green turtles within the BIRNM have small, specific home ranges and core use areas with temporally varying relative selection strengths across habitat types. We conclude the BIRNM marine protected area is providing sufficient protection for immature green turtles, however, habitat protection could be focused in both areas of high space use and in locations where high relative selection values were determined. Ultimately, the methodologies and results presented here may help to design strategies to expand habitat protection for immature green turtles across their greater distribution.","language":"English","publisher":"BMC","doi":"10.1186/s40317-020-00209-9","usgsCitation":"Griffin, L., Smith, B., Cherkiss, M., Crowder, A., Pollock, C.G., Hillis-Starr, Z., Danylchuk, A.J., and Hart, K., 2020, Space use and relative habitat selection for immature green turtles within a Caribbean marine protected area: Animal Biotelemetry, v. 8, 22, 13 p., https://doi.org/10.1186/s40317-020-00209-9.","productDescription":"22, 13 p.","ipdsId":"IP-116004","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":456142,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-020-00209-9","text":"Publisher Index Page"},{"id":376103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States Virgin Islands","state":"St. Croix","otherGeospatial":"Buck Island Reef National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.64750289916992,\n 17.767487103047646\n ],\n [\n -64.59136962890625,\n 17.767487103047646\n ],\n [\n -64.59136962890625,\n 17.80491863487742\n ],\n [\n -64.64750289916992,\n 17.80491863487742\n ],\n [\n -64.64750289916992,\n 17.767487103047646\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2020-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Griffin, Lucas P","contributorId":228796,"corporation":false,"usgs":false,"family":"Griffin","given":"Lucas P","affiliations":[{"id":41510,"text":"Department of Environmental Conservation, University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":792070,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Brian J. 0000-0002-0531-0492","orcid":"https://orcid.org/0000-0002-0531-0492","contributorId":139672,"corporation":false,"usgs":false,"family":"Smith","given":"Brian J.","affiliations":[{"id":12876,"text":"Cherokee Nation Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":792071,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cherkiss, Michael 0000-0002-7802-6791","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":222174,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":792072,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crowder, Andrew 0000-0001-6978-6265","orcid":"https://orcid.org/0000-0001-6978-6265","contributorId":218467,"corporation":false,"usgs":true,"family":"Crowder","given":"Andrew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":792073,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pollock, Clayton G","contributorId":228797,"corporation":false,"usgs":false,"family":"Pollock","given":"Clayton","email":"","middleInitial":"G","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":792074,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hillis-Starr, Zandy","contributorId":179152,"corporation":false,"usgs":false,"family":"Hillis-Starr","given":"Zandy","email":"","affiliations":[],"preferred":false,"id":792075,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Danylchuk, Andy J.","contributorId":138981,"corporation":false,"usgs":false,"family":"Danylchuk","given":"Andy","email":"","middleInitial":"J.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":792076,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":214961,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":792077,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70210903,"text":"70210903 - 2020 - Prioritizing river basins for intensive monitoring and assessment by the US Geological Survey","interactions":[],"lastModifiedDate":"2020-07-03T14:56:34.693731","indexId":"70210903","displayToPublicDate":"2020-07-02T13:07:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1550,"text":"Environmental Modeling & Assessment","onlineIssn":" 1573-296","printIssn":"1420-2026","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing river basins for intensive monitoring and assessment by the US Geological Survey","docAbstract":"

The US Geological Survey (USGS) is currently (2020) integrating its water science programs to better address the nation’s greatest water resource challenges now and into the future. This integration will rely, in part, on data from 10 or more intensively monitored river basins from across the USA. A team of USGS scientists was convened to develop a systematic, quantitative approach to prioritize candidate basins for this monitoring investment to ensure that, as a group, the 10 basins will support the assessment and forecasting objectives of the major USGS water science programs. Candidate basins were the level-4 hydrologic units (HUC04) with some of the smaller HUC04s being combined; median candidate-basin area is 46,600 km2. Candidate basins for the contiguous United States (CONUS) were grouped into 18 hydrologic regions. Ten geospatial variables representing land use, climate change, water use, water-balance components, streamflow alteration, fire risk, and ecosystem sensitivity were selected to rank candidate basins within each of the 18 hydrologic regions. The two highest ranking candidate basins in each of the 18 regions were identified as finalists for selection as “Integrated Water Science Basins”; final selection will consider input from a variety of stakeholders. The regional framework, with only one basin selected per region, ensures that as a group, the basins represent the range in major drivers of the hydrologic cycle. Ranking within each region, primarily based on anthropogenic stressors of water resources, ensures that settings representing important water-resource challenges for the nation will be studied.

","language":"English","publisher":"Springer","doi":"10.1007/s10661-020-08403-1","usgsCitation":"Van Metre, P.C., Qi, S.L., Deacon, J.R., Dieter, C., Driscoll, J.M., Fienen, M.N., Kenney, T.A., Lambert, P.M., Lesmes, D.P., Mason, C., Mueller-Solger, A., Musgrove, M., Painter, J.A., Rosenberry, D.O., Sprague, L.A., Tesoriero, A.J., Windham-Myers, L., and Wolock, D.M., 2020, Prioritizing river basins for intensive monitoring and assessment by the US Geological Survey: Environmental Modeling & Assessment, v. 192, 458, 17 p., https://doi.org/10.1007/s10661-020-08403-1.","productDescription":"458, 17 p.","ipdsId":"IP-114496","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456145,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-020-08403-1","text":"Publisher Index Page"},{"id":436898,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98194QR","text":"USGS data release","linkHelpText":"Data used to prioritize the selection of river basins for intensive monitoring and assessment by the U.S. Geological Survey"},{"id":376102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"contiguous United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 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Texas","interactions":[],"lastModifiedDate":"2020-07-03T14:57:56.659491","indexId":"70210902","displayToPublicDate":"2020-07-02T12:43:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Urban stream syndrome and contaminant uptake in salamanders of Central Texas","docAbstract":"

We studied the ecological health of springs experiencing varying levels of urban development to assess impacts to rare endemic salamanders (Eurycea spp.) of Central Texas. We evaluated measures of invertebrate species richness, water quality, and contaminant uptake by salamanders to determine how springs and their inhabitants were being affected by urban growth and changing land-use patterns. The number of environmental contaminants present and concentrations of contaminants increased in both water and salamander tissues with increasing age of the developments (i.e., years postconstruction) and increasing levels of impervious cover (e.g., roads) in urban watersheds compared with nondeveloped sites. We conclude that urbanization and associated increases in pollutant loading in watersheds can result in a loss of spring biodiversity and the accumulation of persistent and potentially toxic pollutants in salamanders. Although we detected generally low levels of pollutants, the altered water quality and invertebrate composition observed at springs, coupled with the changing hydrology and chronic contaminant exposure inherent in urban landscapes, is cause for concern, with potential implications for the long-term health, survival, and recovery of salamanders.

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To investigate a Florida manatee (Trichechus manatus latirostris) mortality event following a red tide bloom in Southwest Florida, an RNA sequencing experiment was conducted. Gene expression changes in white blood cells were assessed in manatees rescued from a red tide affected area (n = 4) and a control group (n = 7) using RNA sequencing. The genes with the largest fold changes were compared between the two groups to identify molecular pathways related to cellular and disease processes. In total, 591 genes (false discovery rate <0.05) were differentially expressed in the red tide group. Of these, 158 were upregulated and 433 were downregulated. This suggests major changes in white blood cell composition following an exposure to red tide. The most highly upregulated gene, Osteoclast associated 2C immunoglobulin-like receptor (OSCAR), was upregulated 12-fold. This gene is involved in initiating the immune response and maintaining a role in adaptive and innate immunity. The most highly downregulated gene, Piccolo presynaptic cytomatrix protein (PCLO), was downregulated by a factor of 977-fold. This gene is associated with cognitive functioning and neurotransmitter release. Downregulation of this gene in other studies was associated with neuronal loss and neuron synapse dysfunction. Among the cellular pathways that were most affected, immune response, including inflammation, wounds and injuries, cell proliferation, and apoptosis were the most predominant. The pathway with the most differentially expressed genes was the immune response pathway with 98 genes involved, many of them downregulated. Assessing the changes in gene expression associated with red tide exposure enhances our understanding of manatee immune response to the red tide toxins and will aid in the development of red tide biomarkers.

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TThe vast boreal biome plays an important role in the global carbon cycle but is experiencing particularly rapid climate warming, threatening the integrity of valued ecosystems and their component species. We developed a framework and taxonomy to identify climate‐change refugia potential in the North American boreal region, summarizing current knowledge regarding mechanisms, geographic distribution, and landscape indicators. While “terrain‐mediated” refugia will mostly be limited to coastal and mountain regions, the ecological inertia (resistance to external fluctuations) contained in some boreal ecosystems may provide more extensive buffering against climate change, resulting in “ecosystem‐protected” refugia. A notable example is boreal peatlands, which can retain high surface soil moisture and water tables even in the face of drought. Refugia from wildfire are also especially important in the boreal region, which is characterized by active disturbance regimes. Our framework will help identify areas of high refugia potential, and inform ecosystem management and conservation planning in light of climate change.

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Tracking resources that change across space and time is predicted to be a fundamental driver of animal movement [2]. For example, some migratory ungulates (i.e., hooved mammals) closely track the progression of highly nutritious plant green-up, a phenomenon called “green-wave surfing” [3-5]. Yet, general principles describing how the dynamic nature of resources determine movement tactics are lacking [6]. We tested emerging theory that predicts surfing and the existence of migratory behavior will be favored in environments where green-up is fleeting and moves sequentially across large landscapes (i.e., wave-like green-up) [7]. Landscapes exhibiting wave-like patterns of green-up facilitated surfing and explained the existence of migratory behavior across 61 populations of four ungulate species on two continents (n=1,696 individuals). At the species level, foraging benefits were equivalent between tactics, suggesting that each movement tactic is fine tuned to local patterns of plant phenology. For decades, ecologists have sought to understand how animals move to select habitat, commonly defining habitat as a set of static patches [8, 9]. Our findings indicate that animal movement tactics emerge as a function of the flux of resources across space and time, underscoring the need to redefine habitat to include its dynamic attributes. As global habitats continue to be modified by anthropogenic disturbance and climate change [10], our synthesis provides a generalizable framework to understand how animal movement will be influenced by altered patterns of resource phenology.","language":"English","publisher":"Elsevier","doi":"10.1016/j.cub.2020.06.032","usgsCitation":"Aikens, E., Mysterud, A., Merkle, J., Cagnacci, F., Rivrud, I.M., Hebblewhite, M., Hurley, M., Peters, W., Bergen, S., De Groeve, J., Dwinnell, S.P., Gehr, B., Heurich, M., Mark Hewison, A.J., Jarnemo, A., Kjellander, P., Kroschel, M., Licoppe, A., Linnell, J., Merrill, E.H., Middleton, A.D., Morellet, N., Neufeld, L., Ortega, A.C., Parker, K.L., Pedrotti, L., Proffitt, K., Said, S., Sawyer, H., Scurlock, B.M., Signer, J., Stent, P., Sustr, P., Szkorupa, T., Monteith, K., and Kauffman, M., 2020, Wave-like patterns of plant phenology determine ungulate movement tactics: Current Biology, v. 30, no. 17, p. 3444-3449, 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A wildfire near Boulder, Colorado that burned a forested watershed recovering from mining disturbance that occurred 80-160 years ago allowed us to 1) assess arsenic and metal contamination in streams draining the burned area for a five-year period after the wildfire and 2) determine the fire-affected hydrologic drivers that convey arsenic and metals to surface water. Most metal concentrations were low in the circumneutral waters draining the burned area. Water and sediment collected from streams downstream of the burned area had elevated arsenic concentrations during and after post-fire storms. Mining-related deposits were the main source of arsenic to streams. An increased proportion of overland flow relative to infiltration after the fire mobilized arsenic- and metal- rich surface deposits and wildfire ash into streams within and downstream of the burned area. The deposition of this sediment into stream channels resulted in the remobilization of arsenic for the five-year post-fire study period. It is also possible that enhanced subsurface flow after the fire increased contact of water with arsenic-bearing minerals exposed in underground mine workings. Other studies have reported that wildfire ash can be an important source of arsenic and metals to surface waters, but wildfire ash was not an important source of arsenic in this study. Predicted increases in frequency, size, and intensity of wildfires in the western U.S., a region with widely dispersed historical mines, suggest that the intersection of legacy mining and post-wildfire hydrologic response poses an increasing risk for water supplies.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.140635","usgsCitation":"Murphy, S.F., McCleskey, R., Martin, D.A., Holloway, J.M., and Writer, J., 2020, Wildfire-driven changes in hydrology mobilize arsenic and metals from legacy mine waste: Science of the Total Environment, v. 743, 140635, 15 p., https://doi.org/10.1016/j.scitotenv.2020.140635.","productDescription":"140635, 15 p.","ipdsId":"IP-118726","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456160,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.140635","text":"Publisher Index Page"},{"id":436899,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P941BIYS","text":"USGS data release","linkHelpText":"Chemistry of water, stream sediment, wildfire ash, soil, dust, and mine waste for Fourmile Creek Watershed, Colorado, 2010-2019"},{"id":376298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Boulder","otherGeospatial":"Four Mile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.45948028564453,\n 39.98211859887411\n ],\n [\n -105.33416748046875,\n 39.98211859887411\n ],\n [\n -105.33416748046875,\n 40.04049503186035\n ],\n [\n -105.45948028564453,\n 40.04049503186035\n ],\n [\n -105.45948028564453,\n 39.98211859887411\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"743","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":792586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCleskey, R. 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Blaine","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":792587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":168662,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":792588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holloway, JoAnn M. 0000-0003-3603-7668","orcid":"https://orcid.org/0000-0003-3603-7668","contributorId":201855,"corporation":false,"usgs":true,"family":"Holloway","given":"JoAnn","middleInitial":"M.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":792589,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Writer, Jeffrey H.","contributorId":203440,"corporation":false,"usgs":false,"family":"Writer","given":"Jeffrey H.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":792590,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211042,"text":"70211042 - 2020 - Report on the workshop ‘Next Steps in Developing Nature Futures’","interactions":[],"lastModifiedDate":"2020-07-13T13:36:18.200299","indexId":"70211042","displayToPublicDate":"2020-07-02T08:26:09","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Report on the workshop ‘Next Steps in Developing Nature Futures’","docAbstract":"The workshop ‘New Narratives for Nature: operationalizing the IPBES Nature Futures Scenarios’ was organised by the IPBES task force on scenarios and models and hosted by the Institute for Global Environmental Strategies (IGES), with support from the research team on “Predicting and Assessing Natural Capital and Ecosystem Services through an Integrated Social-Ecological Systems Approach (PANCES)” based at the University of Tokyo, the Research Institute for Humanity and Nature (RIHN), and the United Nations University, with generous financial support from the Ministry of the Environment of Japan. \n\nDue to the COVID-19 virus outbreak, most task force members participated through virtual means, with a subset of task force members meeting in person in Japan.\n\nThe aim of the workshop was to build on the Nature Futures Framework (NFF) and on the ‘nature futures’ participatory scenario-development work initiated by the IPBES expert group on scenarios and models in the first IPBES work programme. This workshop aims to further elaborate the pre-workshop scenario narratives and to enrich discussions on the NFF. The workshop also served to start working on a more detailed task force work plan.\n\nThese aims were achieved through:\n• Task force sessions on the further formulation of the Nature Futures narratives.\n• Task force sessions on the cross-comparison of draft narratives and the further elaboration of the historical-present narrative.\n• Organisational sessions to begin the drafting of sub-deliverable-specific work plans.\n• In parallel to the task force workshop, collaborative sessions between the task force and Japanese researchers took place to discuss the application of the Nature Futures Framework at the national scale, using existing national level scenarios from Japan.\n• A public seminar, in Japan, for a wider audience introducing the scenarios and models task force’s work, the concept of the Nature Futures Framework, and fostered discussions on the concept of transformative change.\n\nSummary of outputs of the workshop in Japan\n• 6 NEW scenario narratives drafts – an evolution of the pre-workshop work using the narrative templates, into a more coherent set of narratives fitting their locations in the Nature Futures Framework, including some illustrative visualisations. \n• A cross-comparison table – to identify the core similarities and differences across the 6 new narratives (including single narrative-between-narrative comparisons).\n• A discussion on how to continue further development, requiring identifying pathways to complete the 6 new narratives.\n• 1 historical-to-present narrative draft – also an evolution of work done prior to the workshop. The task force has yet to synthesize and shorten this draft, ensuring linkages with topics detailed in the 6 new narratives into a more digestible level.\n• Elaboration of a follow-up plan for further development of the narratives, post-workshop, through a “buddy” system of in-depth online discussions per and between narratives. \n• 1 Japan case study – on fitting national level scenarios into the Nature Futures Framework. A summary will be shared by the team who worked closely on this with the PANCES partners, which we expect will give interesting insights to the cross-scale application of the Nature Futures Framework.\n• Detailed work plan implementation drafts (ongoing post workshop in sub-groups).","language":"English","publisher":"PBL Netherlands Environmental Assessment Agency","collaboration":"Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services; And Institute for Global Environmental Strategies (IGES), University of Tokyo, Research Institute for Humanity and Nature (RIHN), United Nations University, Ministry of the Environment of Japan","usgsCitation":"Schoolenberg, M., Okayasu, S., Alkemade, R., Krijgsman, A., Dutra de Aguiar, A.P., Hashimoto, S., Lundquist, C.J., Pereira, L., Peterson, G., Armenteras, D., Cheung, W.W., Diaw, M.C., Duran, A.P., Gasalla, M., Halouani, G., Harrisson, P., Karlsson-Vinkhuyzen, S., Kim, H., Kuiper, J.J., Miller, B., Takahashi, Y., and Pichs, R., 2020, Report on the workshop ‘Next Steps in Developing Nature Futures’, i, 37 p.","productDescription":"i, 37 p.","ipdsId":"IP-118520","costCenters":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":376289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":376282,"type":{"id":15,"text":"Index Page"},"url":"https://www.pbl.nl/en/publications/report-on-the-workshop-%E2%80%98new-narratives-for-nature-operationalizing-the-ipbes-nature-futures-scenarios%E2%80%99"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schoolenberg, Machteld","contributorId":228931,"corporation":false,"usgs":false,"family":"Schoolenberg","given":"Machteld","email":"","affiliations":[{"id":41529,"text":"PBL","active":true,"usgs":false}],"preferred":false,"id":792551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Okayasu, Sana","contributorId":228932,"corporation":false,"usgs":false,"family":"Okayasu","given":"Sana","affiliations":[{"id":41529,"text":"PBL","active":true,"usgs":false}],"preferred":false,"id":792552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alkemade, Rob 0000-0001-8761-1768","orcid":"https://orcid.org/0000-0001-8761-1768","contributorId":202614,"corporation":false,"usgs":false,"family":"Alkemade","given":"Rob","email":"","affiliations":[{"id":36496,"text":"PBL Netherlands Environmental Assessment Agency","active":true,"usgs":false}],"preferred":false,"id":792559,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krijgsman, Amanda","contributorId":228933,"corporation":false,"usgs":false,"family":"Krijgsman","given":"Amanda","email":"","affiliations":[{"id":41529,"text":"PBL","active":true,"usgs":false}],"preferred":false,"id":792553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dutra de Aguiar, Ana Paula","contributorId":228934,"corporation":false,"usgs":false,"family":"Dutra de Aguiar","given":"Ana","email":"","middleInitial":"Paula","affiliations":[],"preferred":false,"id":792554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hashimoto, Shizuka","contributorId":228935,"corporation":false,"usgs":false,"family":"Hashimoto","given":"Shizuka","email":"","affiliations":[],"preferred":false,"id":792555,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lundquist, Carolyn J.","contributorId":213140,"corporation":false,"usgs":false,"family":"Lundquist","given":"Carolyn","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":792556,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pereira, Laura M.","contributorId":228936,"corporation":false,"usgs":false,"family":"Pereira","given":"Laura","middleInitial":"M.","affiliations":[],"preferred":false,"id":792557,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Peterson, Garry","contributorId":228937,"corporation":false,"usgs":false,"family":"Peterson","given":"Garry","email":"","affiliations":[],"preferred":false,"id":792558,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Armenteras, Dolors","contributorId":228938,"corporation":false,"usgs":false,"family":"Armenteras","given":"Dolors","email":"","affiliations":[],"preferred":false,"id":792560,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cheung, William W. L.","contributorId":221038,"corporation":false,"usgs":false,"family":"Cheung","given":"William","email":"","middleInitial":"W. L.","affiliations":[],"preferred":false,"id":792561,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Diaw, Mariteuw Chimere","contributorId":228939,"corporation":false,"usgs":false,"family":"Diaw","given":"Mariteuw","email":"","middleInitial":"Chimere","affiliations":[],"preferred":false,"id":792563,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Duran, America Paz","contributorId":228940,"corporation":false,"usgs":false,"family":"Duran","given":"America","email":"","middleInitial":"Paz","affiliations":[],"preferred":false,"id":792564,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gasalla, Maria","contributorId":228941,"corporation":false,"usgs":false,"family":"Gasalla","given":"Maria","email":"","affiliations":[],"preferred":false,"id":792565,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Halouani, Ghassen","contributorId":228942,"corporation":false,"usgs":false,"family":"Halouani","given":"Ghassen","email":"","affiliations":[],"preferred":false,"id":792566,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Harrisson, Paula","contributorId":228943,"corporation":false,"usgs":false,"family":"Harrisson","given":"Paula","email":"","affiliations":[],"preferred":false,"id":792567,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Karlsson-Vinkhuyzen, Sylvia","contributorId":228944,"corporation":false,"usgs":false,"family":"Karlsson-Vinkhuyzen","given":"Sylvia","email":"","affiliations":[],"preferred":false,"id":792568,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Kim, HyeJin","contributorId":228945,"corporation":false,"usgs":false,"family":"Kim","given":"HyeJin","email":"","affiliations":[],"preferred":false,"id":792569,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Kuiper, Jan J.","contributorId":222013,"corporation":false,"usgs":false,"family":"Kuiper","given":"Jan","email":"","middleInitial":"J.","affiliations":[{"id":40465,"text":"Stockholm Resilience Centre, Stockholm University","active":true,"usgs":false}],"preferred":false,"id":792570,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Miller, Brian W. 0000-0003-1716-1161 bwmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":195418,"corporation":false,"usgs":true,"family":"Miller","given":"Brian W.","email":"bwmiller@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":false,"id":792571,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Takahashi, Yasuo","contributorId":221515,"corporation":false,"usgs":false,"family":"Takahashi","given":"Yasuo","email":"","affiliations":[],"preferred":false,"id":792572,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Pichs, Ramon","contributorId":228957,"corporation":false,"usgs":false,"family":"Pichs","given":"Ramon","email":"","affiliations":[],"preferred":false,"id":792595,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70219051,"text":"70219051 - 2020 - Fish growth rates and lake sulphate explain variation in mercury levels in ninespine stickleback (Pungitius pungitius) on the Arctic Coastal Plain of Alaska","interactions":[],"lastModifiedDate":"2021-03-22T13:16:14.021201","indexId":"70219051","displayToPublicDate":"2020-07-02T08:11:09","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Fish growth rates and lake sulphate explain variation in mercury levels in ninespine stickleback (Pungitius pungitius) on the Arctic Coastal Plain of Alaska","docAbstract":"

Mercury concentrations in freshwater food webs are governed by complex biogeochemical and ecological interactions that spatially vary and are often mediated by climate. The Arctic Coastal Plain of Alaska (ACP) is a heterogeneous, lake-rich landscape where variability in mercury accumulation is poorly understood. Earlier research indicated that the level of catchment influence on lakes varied spatially on the ACP, and affected mercury accumulation in lake sediments. This work sought to determine drivers of spatial variation in mercury accumulation in lake food webs on the ACP. Three lakes that were a priori identified as “high catchment influence” (Reindeer Camp region) and three lakes that were a priori identified as “low catchment influence” (Atqasuk region) were sampled, and variability in water chemistry, food web ecology, and mercury accumulation was investigated. Among-lake differences in ninespine stickleback (Pungitius pungitius) length-adjusted methylmercury concentrations were significantly explained by sulphate concentration in lake water, a tracer of catchment runoff input. This effect was mediated by fish growth, which had no pattern between regions. Together, lake water sulphate concentration and fish age-at-size (proxy for growth) accounted for nearly all of the among-lake variability in length-adjusted methylmercury concentrations in stickleback (R2adj = 0.94, p < 0.01). The percentage of total mercury as methylmercury (a proxy for net Hg methylation) was higher in sediments of more autochthonous, “low catchment influence” lakes (p < 0.05), and in the periphyton of more allochthonous, “high catchment influence” lakes (p < 0.05). The results indicate that dominant sources of primary production (littoral macrophyte/biofilm vs. pelagic phytoplankton) and food web structure (detrital vs. grazing) are regulated by catchment characteristics on the ACP, and that this ultimately influences the amount of methylmercury in the aquatic food web. These results have important implications for predicting future mercury concentrations in fish in lakes where fish growth rates and catchment inputs may change in response to a changing climate.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.140564","usgsCitation":"Burke, S.M., Zimmerman, C.E., Laske, S.M., Koch, J.C., Derry, A.M., Guernon, S., Branfireun, B.A., and Swanson, H.K., 2020, Fish growth rates and lake sulphate explain variation in mercury levels in ninespine stickleback (Pungitius pungitius) on the Arctic Coastal Plain of Alaska: Science of the Total Environment, v. 743, 140564, 11 p., https://doi.org/10.1016/j.scitotenv.2020.140564.","productDescription":"140564, 11 p.","ipdsId":"IP-119948","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":384536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160.15869140625,\n 69.31832006949072\n ],\n [\n -151.50146484375,\n 69.31832006949072\n ],\n [\n -151.50146484375,\n 71.51794480424527\n ],\n [\n -160.15869140625,\n 71.51794480424527\n ],\n [\n -160.15869140625,\n 69.31832006949072\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"743","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burke, Samantha M.","contributorId":203348,"corporation":false,"usgs":false,"family":"Burke","given":"Samantha","email":"","middleInitial":"M.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":812593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":812594,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":812595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":812596,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Derry, Allison M. 0000-0001-5768-8027","orcid":"https://orcid.org/0000-0001-5768-8027","contributorId":255569,"corporation":false,"usgs":false,"family":"Derry","given":"Allison","email":"","middleInitial":"M.","affiliations":[{"id":24488,"text":"Universite du Quebec a Montreal","active":true,"usgs":false}],"preferred":false,"id":812597,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Guernon, Stephanie 0000-0003-0316-496X","orcid":"https://orcid.org/0000-0003-0316-496X","contributorId":255570,"corporation":false,"usgs":false,"family":"Guernon","given":"Stephanie","email":"","affiliations":[{"id":24488,"text":"Universite du Quebec a Montreal","active":true,"usgs":false}],"preferred":false,"id":812598,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Branfireun, Brian A.","contributorId":203349,"corporation":false,"usgs":false,"family":"Branfireun","given":"Brian","email":"","middleInitial":"A.","affiliations":[{"id":33186,"text":"Western University","active":true,"usgs":false}],"preferred":false,"id":812599,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Swanson, Heidi K.","contributorId":203350,"corporation":false,"usgs":false,"family":"Swanson","given":"Heidi","email":"","middleInitial":"K.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":812600,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216109,"text":"70216109 - 2020 - Characterizing benthic macroinvertebrate and algal biological condition gradient models for California wadeable Streams, USA","interactions":[],"lastModifiedDate":"2020-11-05T14:41:53.835194","indexId":"70216109","displayToPublicDate":"2020-07-02T08:03:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing benthic macroinvertebrate and algal biological condition gradient models for California wadeable Streams, USA","docAbstract":"

The Biological Condition Gradient (BCG) is a conceptual model that describes changes in aquatic communities under increasing levels of anthropogenic stress. The BCG helps decision-makers connect narrative water quality goals (e.g., maintenance of natural structure and function) to quantitative measures of ecological condition by linking index thresholds based on statistical distributions (e.g., percentiles of reference distributions) to expert descriptions of changes in biological condition along disturbance gradients. As a result, the BCG may be more meaningful to managers and the public than indices alone. To develop a BCG model, biological response to stress is divided into 6 levels of condition, represented as changes in biological structure (abundance and diversity of pollution sensitive versus tolerant taxa) and function. We developed benthic macroinvertebrate (BMI) and algal BCG models for California perennial wadeable streams to support interpretation of percentiles of reference-based thresholds for bioassessment indices (i.e., the California Stream Condition Index [CSCI] for BMI and the Algal Stream Condition Index [ASCI] for diatoms and soft-bodied algae). Two panels (one of BMI ecologists and the other of algal ecologists) each calibrated a general BCG model to California wadeable streams by first assigning taxa to specific tolerance and sensitivity attributes, and then independently assigning test samples (264 BMI and 248 algae samples) to BCG Levels 1–6. Consensus on the assignments was developed within each assemblage panel using a modified Delphi method. Panels then developed detailed narratives of changes in BMI and algal taxa that correspond to the 6 BCG levels. Consensus among experts was high, with 81% and 82% expert agreement within 0.5 units of assigned BCG level for BMIs and algae, respectively. According to both BCG models, the 10th percentiles index scores at reference sites corresponded to a BCG Level 3, suggesting that this type of threshold would protect against moderate changes in structure and function while allowing loss of some sensitive taxa. The BCG provides a framework to interpret changes in aquatic biological condition along a gradient of stress. The resulting relationship between index scores and BCG levels and narratives can help decision-makers select thresholds and communicate how these values protect aquatic life use goals.

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The Planchón Peteroa Volcanic Complex (PPVC) is located on the border of Chile and Argentina, and is one of the most active volcanic systems in the Andes. Holocene activity has included magma-water interaction with an evolving series of crater lakes, mainly sourced from Peteroa volcano. This study examines data from the 2018/19 eruption, together with the volcanic history of the PPVC, to elucidate the complex interplay between magmatic activity and summit water and ice. From February 2016 to mid-2019, three seismic swarms occurred in the PPVC, preceding the explosive eruption from September 2018 to April 2019. The activity originated from a small vent nested within the easternmost crater, the most active portion of the complex (Peteroa). The explosions interacted with a crater lake, producing ash plumes up to 2 km above the crater and building a small tephra cone. To investigate the eruption mechanisms, we performed remote sensing analysis of plume dispersal, thermal anomalies and ground deformation, and characterized the volcanic products, including grain size, componentry, morphology, internal textures, composition and mineralogy. Our results suggest that the precursory seismicity beginning in 2016 was related to the intrusion of a new magma batch that reached the surface during the 2018/19 eruption. The eruption was also preceded by thermal anomalies, geomorphic changes and increased hydrothermal activity at the surface, though without any ground deformation recognized through radar interferometry (InSAR). The eruption initially produced predominantly recycled ash (phreatic activity), then evolved to increasing proportions of juvenile magma (phreatomagmatic) by April 2019. The juvenile clasts had a trachyandesite composition (~59 wt% SiO2), with vesicular and dense scoria containing plagioclase and pyroxene. The ash surfaces show external quenching cracks and step fractures consistent with phreatomagmatic fragmentation within the active crater lake. Textural characteristics also point to a slowly ascending batch of magma that was relatively viscous by the time it interacted with water in the crater lake. Notably, these juvenile particles are distinctive from the pre-2018 products. Ash erupted from 2010/11 did not contain recognizable juvenile material, and is inferred to have been a mainly phreatic eruption. Our findings suggest that the interplay between phreatic and phreatomagmatic eruptions fed by small magma batches intruding at shallow levels characterize much of the eruptive behavior of the PPVC during the last three decades. Multi-parametric assessment is a powerful tool to discriminate between phreatic and phreatomagmatic eruptions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2020.106984","usgsCitation":"Romero, J.E., Aguilera, F., Delgado, F., Guzman, D., Van Eaton, A.R., Luengo, N., Caro, J., Bustillos, J., Guevara, A., Holbik, S., Tormey, D., and Zegarra, I., 2020, Combining ash analyses with remote sensing to identify juvenile magma involvement and fragmentation mechanisms during the 2018/19 small eruption of Peteroa volcano (Southern Andes): Journal of Volcanology and Geothermal Research, v. 405, 106984, 20 p., https://doi.org/10.1016/j.jvolgeores.2020.106984.","productDescription":"106984, 20 p.","ipdsId":"IP-119001","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":384925,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","otherGeospatial":"Southern Andes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n 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Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Development of a new open-source tool to map burned area and burn severity","docAbstract":"

Accurate and complete geospatial fire occurrence records are important in determining postfire effects, emissions, hazards, and fuel loading inventories. Currently, the Monitoring Trends in Burn Severity (MTBS) project maps the fire perimeter and burn severity of all large fires on public lands. Although the MTBS project maps a large proportion of the fire acreage, it maps a smaller proportion of the actual number of fires in the United States, thereby creating a data gap. To fill this data gap, fire scientists at the U.S. Geological Survey (USGS) Earth Resources Observation and Science Center (EROS; Sioux Falls, South Dakota) proposed creating an open-source Fire Mapping Tool (FMT; available at https://mtbs.gov/qgis-fire-mapping-tool) as part of a two-phase National Aeronautics and Space Administration (NASA) Applied Fire Science Program grant. Phase II developed the FMT to map burn perimeters and severity not included in the MTBS database. This paper will focus on Phase II and will explain the algorithms that enhance the FMT’s functionality, demonstrate fire mapping procedures, and provide an example comparison between MTBS analyst fire products and those mapped using the FMT. The overall goal in the production of the FMT was to provide a freely available tool that can be used to map fires anywhere in the world.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the fire continuum- Preparing for the future of wildland fire","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"U.S. Forest Service","usgsCitation":"Picotte, J.J., 2020, Development of a new open-source tool to map burned area and burn severity, in Proceedings of the fire continuum- Preparing for the future of wildland fire, p. 182-194.","productDescription":"13 p.","startPage":"182","endPage":"194","ipdsId":"IP-097770","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":377462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":377460,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.fs.fed.us/rm/pubs_series/rmrs/proc/rmrs_p078.pdf"}],"country":"United States","state":"Washington","otherGeospatial":"Paradise Fire","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.16404724121094,\n 47.5369059030354\n ],\n [\n -123.94020080566408,\n 47.62467785241324\n ],\n [\n -123.87187957763672,\n 47.68018294648414\n ],\n [\n -123.88011932373045,\n 47.70352370383532\n ],\n [\n -123.94191741943358,\n 47.674866264152534\n ],\n [\n -123.98929595947264,\n 47.64943116129891\n ],\n [\n -124.07718658447266,\n 47.636246278753234\n ],\n [\n -124.16130065917969,\n 47.60500565066204\n ],\n [\n -124.20387268066405,\n 47.5820839916191\n ],\n [\n -124.23099517822266,\n 47.56216409801383\n ],\n [\n -124.16439056396483,\n 47.535746978239125\n ],\n [\n -124.16404724121094,\n 47.5369059030354\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":796088,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70211681,"text":"70211681 - 2020 - The potential of using dynamic strains in earthquake early warning applications","interactions":[],"lastModifiedDate":"2020-09-10T20:25:08.380546","indexId":"70211681","displayToPublicDate":"2020-07-01T17:56:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"The potential of using dynamic strains in earthquake early warning applications","docAbstract":"

We investigate the potential of using borehole strainmeter data from the Network of the Americas (NOTA) and the U.S. Geological Survey networks to estimate earthquake moment magnitudes for earthquake early warning (EEW) applications. We derive an empirical equation relating peak dynamic strain, earthquake moment magnitude, and hypocentral distance, and investigate the effects of different types of instrument calibration on model misfit. We find that raw (uncalibrated) strains fit the model as accurately as calibrated strains. We test the model by estimating moment magnitudes of the largest two earthquakes in the July 2019 Ridgecrest earthquake sequence—the M 6.4 foreshock and the M 7.1 mainshock—using two strainmeters located within ∼50  km of the rupture. In both the cases, the magnitude based on the dynamic strain component is within ∼0.1–0.4 magnitude units of the catalog moment magnitude. We then compare the temporal evolution of our strain‐derived magnitudes for the largest two Ridgecrest events to the real‐time performance of the ShakeAlert EEW System (SAS). The final magnitudes from NOTA borehole strainmeters are close to SAS real‐time estimates for the M 6.4 foreshock, and significantly more accurate for the M 7.1 mainshock.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190385","usgsCitation":"Farghal, N.S., Barbour, A.J., and Langbein, J., 2020, The potential of using dynamic strains in earthquake early warning applications: Seismological Research Letters, v. 91, no. 5, p. 2817-2827, https://doi.org/10.1785/0220190385.","productDescription":"11 p.","startPage":"2817","endPage":"2827","ipdsId":"IP-112135","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":377141,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.158203125,\n 32.54681317351514\n ],\n [\n -114.345703125,\n 32.76880048488168\n ],\n [\n -114.345703125,\n 34.34343606848294\n ],\n [\n -120.05859375,\n 39.232253141714885\n ],\n [\n -120.14648437499999,\n 41.96765920367816\n ],\n [\n -119.61914062499999,\n 48.83579746243093\n ],\n [\n -123.96972656249999,\n 49.38237278700955\n ],\n [\n -126.3427734375,\n 49.866316729538674\n ],\n [\n -127.08984375000001,\n 48.22467264956519\n ],\n [\n -124.8486328125,\n 47.39834920035926\n ],\n [\n -124.76074218749999,\n 44.74673324024678\n ],\n [\n -125.33203125,\n 41.343824581185686\n ],\n [\n -124.01367187499999,\n 38.238180119798635\n ],\n [\n -121.728515625,\n 35.28150065789119\n ],\n [\n -119.66308593749999,\n 33.7243396617476\n ],\n [\n -117.158203125,\n 32.54681317351514\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Farghal, Noha Sameh Ahmed 0000-0001-8423-5066","orcid":"https://orcid.org/0000-0001-8423-5066","contributorId":237040,"corporation":false,"usgs":true,"family":"Farghal","given":"Noha","email":"","middleInitial":"Sameh Ahmed","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":795045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barbour, Andrew J 0000-0001-6473-5493 abarbour@usgs.gov","orcid":"https://orcid.org/0000-0001-6473-5493","contributorId":237041,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew","email":"abarbour@usgs.gov","middleInitial":"J","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":795046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langbein, John 0000-0002-7821-8101","orcid":"https://orcid.org/0000-0002-7821-8101","contributorId":212735,"corporation":false,"usgs":true,"family":"Langbein","given":"John","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":795047,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228337,"text":"70228337 - 2020 - Living on the edge: Multi-scale analyses of bird habitat use in coastal marshes of Barataria Basin, Louisiana, USA","interactions":[],"lastModifiedDate":"2022-02-09T22:45:53.971165","indexId":"70228337","displayToPublicDate":"2020-07-01T16:38:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Living on the edge: Multi-scale analyses of bird habitat use in coastal marshes of Barataria Basin, Louisiana, USA","docAbstract":"

Coastal marsh loss, combined with expected sea-level rise, will cause inundation and extensive shifts to vegetation and salinity regimes that may affect the bird species dependent on coastal ecosystems worldwide. Within coastal marsh habitats, birds provide key targets for coastal management goals. However, limited information on bird-habitat relationships within coastal marshes inhibits the development of restoration projects targeted to bird species. We surveyed birds bi-monthly within Barataria Basin, LA from July 2014 to December 2015 to compare their use between fresh and saline coastal marshes. Additionally, we examined habitat use at finer spatial scales to assess preference for marsh edge microhabitats. Edge habitat supported 1.8 times more bird species (guild) richness than emergent and open water habitat. We concluded that future modelling efforts would be improved if models incorporate edge effects for birds in coastal marshes that extend 20 m from emergent vegetation into open water, with a reduced effect if marsh types convert from fresh to saline. Our data will be useful to simulate the effects of changes in marsh type, area, and edge on habitat quality for birds in coastal Louisiana and will inform habitat restoration and management decisions aimed at optimizing bird use.

","language":"English","publisher":"Springer","doi":"10.1007/s13157-020-01324-2","usgsCitation":"Patton, B., Nyman, J.A., and La Peyre, M., 2020, Living on the edge: Multi-scale analyses of bird habitat use in coastal marshes of Barataria Basin, Louisiana, USA: Wetlands, v. 40, p. 2041-2054, https://doi.org/10.1007/s13157-020-01324-2.","productDescription":"14 p.","startPage":"2041","endPage":"2054","ipdsId":"IP-098169","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499826,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/agrnr_pubs/602","text":"External Repository"},{"id":395743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Barataria Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.8349609375,\n 28.714678586705976\n ],\n [\n -89.033203125,\n 28.714678586705976\n ],\n [\n -89.033203125,\n 30.32547125932808\n ],\n [\n -90.8349609375,\n 30.32547125932808\n ],\n [\n -90.8349609375,\n 28.714678586705976\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2020-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Patton, Brett 0000-0002-7396-3452 pattonb@usgs.gov","orcid":"https://orcid.org/0000-0002-7396-3452","contributorId":5458,"corporation":false,"usgs":true,"family":"Patton","given":"Brett","email":"pattonb@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":833827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nyman, J. A.","contributorId":275213,"corporation":false,"usgs":false,"family":"Nyman","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":833828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833829,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211872,"text":"70211872 - 2020 - Regionally continuous Miocene rhyolites beneath the eastern Snake River Plain reveal localized flexure at its western margin: Idaho National Laboratory and vicinity","interactions":[],"lastModifiedDate":"2020-12-15T20:23:40.067951","indexId":"70211872","displayToPublicDate":"2020-07-01T16:07:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6000,"text":"The Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"Regionally continuous Miocene rhyolites beneath the eastern Snake River Plain reveal localized flexure at its western margin: Idaho National Laboratory and vicinity","docAbstract":"The eastern Snake River Plain (ESRP) is a northeast-trending topographic basin interpreted to be the result of the time-transgressive track of the North American plate above the Yellowstone hotspot. The track is defined by the age progression of silicic volcanic rocks exposed along the margins of the ESRP. However, the bulk of these silicic rocks are buried under 1 to 3 kilometers of younger basalts. Here, silicic volcanic rocks recovered from boreholes that penetrate below the basalts, including INEL-1, WO-2 and new deep borehole USGS-142, are correlated with one another and to surface exposures to assess various models for ESRP subsidence. These correlations are established on U/Pb zircon and 40Ar/39Ar sanidine age determinations, phenocryst assemblages, major and trace element geochemistry, δ18O isotopic data from selected phenocrysts, and initial εHf values of zircon. These data suggest a correlation of: (1) the newly documented 8.1 ± 0.2 Ma rhyolite of Butte Quarry (sample 17KS03), exposed near Arco, Idaho to the upper-most Picabo volcanic field rhyolites found in borehole INEL-1; (2) the 6.73 ± 0.02 Ma East Arco Hills rhyolite (sample 16KS02) to the Blacktail Creek Tuff, which was also encountered at the bottom of borehole WO-2; and (3) the 6.42 ± 0.07 Ma rhyolite of borehole USGS-142 to the Walcott Tuff B encountered in deep borehole WO-2. These results show that rhyolites found along the western margin of the ESRP dip ~20º south-southeast toward the basin axis, and then gradually tilt less steeply in the subsurface as the axis is approached. This subsurface pattern of tilting is consistent with a previously proposed crustal flexural model of subsidence based only on surface exposures, but is inconsistent with subsidence models that require accommodation of ESRP subsidence on either a major normal fault or strike-slip fault.","language":"English","publisher":"Rocky Mountain Association of Geologists","doi":"10.31582/rmag.mg.57.3.241","usgsCitation":"Schusler, K.L., Pearson, D.M., McCurry, M.J., Bartholomay, R.C., and Anders, M.H., 2020, Regionally continuous Miocene rhyolites beneath the eastern Snake River Plain reveal localized flexure at its western margin: Idaho National Laboratory and vicinity: The Mountain Geologist, v. 57, no. 3, p. 241-270, https://doi.org/10.31582/rmag.mg.57.3.241.","productDescription":"30 p.","startPage":"241","endPage":"270","ipdsId":"IP-112371","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":377936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.18002319335938,\n 43.41302868475145\n ],\n [\n -111.93145751953125,\n 43.41302868475145\n ],\n [\n -111.93145751953125,\n 43.55651037504758\n ],\n [\n -112.18002319335938,\n 43.55651037504758\n ],\n [\n -112.18002319335938,\n 43.41302868475145\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Schusler, Kyle L.","contributorId":237858,"corporation":false,"usgs":false,"family":"Schusler","given":"Kyle","email":"","middleInitial":"L.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":795484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearson, David M.","contributorId":237860,"corporation":false,"usgs":false,"family":"Pearson","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":795485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCurry, Michael J.","contributorId":237861,"corporation":false,"usgs":false,"family":"McCurry","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":795486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":795487,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anders, Mark H.","contributorId":237862,"corporation":false,"usgs":false,"family":"Anders","given":"Mark","email":"","middleInitial":"H.","affiliations":[{"id":39266,"text":"St. Lawrence University","active":true,"usgs":false}],"preferred":false,"id":795488,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211964,"text":"70211964 - 2020 - Wildfire-driven forest conversion in western North American landscapes","interactions":[],"lastModifiedDate":"2020-08-26T19:34:40.015956","indexId":"70211964","displayToPublicDate":"2020-07-01T16:03:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Wildfire-driven forest conversion in western North American landscapes","docAbstract":"

Changing disturbance regimes and climate can overcome forest ecosystem resilience. Following high-severity fire, forest recovery may be compromised by lack of tree seed sources, warmer and drier postfire climate, or short-interval reburning. A potential outcome of the loss of resilience is the conversion of the prefire forest to a different forest type or nonforest vegetation. Conversion implies major, extensive, and enduring changes in dominant species, life forms, or functions, with impacts on ecosystem services. In the present article, we synthesize a growing body of evidence of fire-driven conversion and our understanding of its causes across western North America. We assess our capacity to predict conversion and highlight important uncertainties. Increasing forest vulnerability to changing fire activity and climate compels shifts in management approaches, and we propose key themes for applied research coproduced by scientists and managers to support decision-making in an era when the prefire forest may not return.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biaa061","usgsCitation":"Coop, J.D., Parks, S.A., Stevens-Rumann, C., Crausbay, S.D., Higuera, P.E., Hurteau, M., Tepley, A.J., Whitman, E., Assal, T.J., Collins, B.M., Davis, K.T., Dobrowski, S., Falk, D.A., Fornwalt, P.J., Fule, P.Z., Harvey, B.J., Kane, V.R., Littlefield, C.E., Margolis, E.Q., North, M., Parisien, M., Prichard, S., and Rodman, K., 2020, Wildfire-driven forest conversion in western North American landscapes: BioScience, v. 70, no. 8, p. 659-673, https://doi.org/10.1093/biosci/biaa061.","productDescription":"15 p.","startPage":"659","endPage":"673","ipdsId":"IP-114399","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":456167,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biaa061","text":"Publisher Index 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Washington","active":true,"usgs":false}],"preferred":false,"id":795995,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Rodman, Kyle C.","contributorId":238090,"corporation":false,"usgs":false,"family":"Rodman","given":"Kyle C.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":795996,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70210894,"text":"sir20205064 - 2020 - A summary of water-quality monitoring in San Francisco Bay in water year 2017","interactions":[],"lastModifiedDate":"2020-07-01T21:11:28.152523","indexId":"sir20205064","displayToPublicDate":"2020-07-01T12:33:01","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations 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This report summarizes the activities of the U.S. Geological Survey (USGS) San Francisco Bay Water-Quality Monitoring and Sediment Transport Project during water year 2017, including an explanation of methods employed, stations operated, and a graphical summary of data for the period of record for stations operational in water year 2017. In cooperation with partner agencies, the USGS maintains a network of sensors that continuously and autonomously measures water-quality parameters in San Francisco Bay including water temperature, specific conductance, turbidity, and suspended-sediment concentration. Data are collected at several locations in the estuary by a network of water-quality sondes sampled at 15-minute intervals. Methods of data collection are presented along with documentation of the regression models utilized to estimate suspended-sediment concentration from observed turbidity, a commonly utilized surrogate to estimate suspended-sediment concentration. The goals of the data collection effort are to (1) obtain long-term, high-frequency, and high-quality data to describe San Francisco Bay water quality; (2) make the data publicly available on the USGS National Water Information System data portal; and (3) help improve understanding of the spatial and temporal variability of water quality in the estuary, informing management decisions regarding restoration, water supply, navigation, and ecology.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205064","usgsCitation":"Livsey, D., and Downing-Kunz, M., 2020, A summary of water-quality monitoring in San Francisco Bay in water year 2017: U.S. Geological Survey Scientific Investigations Report 2020–5064, 78 p., https://doi.org/10.3133/sir20205064.","productDescription":"Report: vi, 78 p.; Data Release","numberOfPages":"78","onlineOnly":"Y","ipdsId":"IP-104269","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":376068,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","linkHelpText":"National Water Information System"},{"id":376066,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5064/coverthb.jpg"},{"id":376067,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5064/sir20205064.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.62390136718749,\n 37.35050947036205\n ],\n [\n -121.7340087890625,\n 37.35050947036205\n ],\n [\n -121.7340087890625,\n 38.22307753495298\n ],\n [\n -122.62390136718749,\n 38.22307753495298\n ],\n [\n -122.62390136718749,\n 37.35050947036205\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2020-07-01","noUsgsAuthors":false,"publicationDate":"2020-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Livsey, Daniel N. 0000-0002-2028-6128 dlivsey@usgs.gov","orcid":"https://orcid.org/0000-0002-2028-6128","contributorId":181870,"corporation":false,"usgs":true,"family":"Livsey","given":"Daniel","email":"dlivsey@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Downing-Kunz, Maureen A. 0000-0002-4879-0318 mdowning-kunz@usgs.gov","orcid":"https://orcid.org/0000-0002-4879-0318","contributorId":3690,"corporation":false,"usgs":true,"family":"Downing-Kunz","given":"Maureen","email":"mdowning-kunz@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792012,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221909,"text":"70221909 - 2020 - Imprint of regional oceanography on foraminifera of eastern Pacific Coral Reefs","interactions":[],"lastModifiedDate":"2021-07-15T09:54:09.707186","indexId":"70221909","displayToPublicDate":"2020-07-01T12:05:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2294,"text":"Journal of Foraminiferal Research","active":true,"publicationSubtype":{"id":10}},"title":"Imprint of regional oceanography on foraminifera of eastern Pacific Coral Reefs","docAbstract":"

The marginal marine environments of the eastern tropical Pacific (ETP) serve as an ideal natural laboratory to study how oceanographic and climatic variability influence coral-reef ecosystems. Reefs along the Pacific coast of Panamá span a natural gradient of nutrients, pH, and temperature as a result of stronger seasonal upwelling in the Gulf of Panamá relative to the Gulf of Chiriquí. The ecosystems are not only influenced by spatial and seasonal variations in oceanography but are affected by the climatic variability of the El Niño-Southern Oscillation (ENSO). Foraminifera can be robust indicators of ecosystem condition because the composition of their assemblages and the geochemistry of their tests can change rapidly in response to environmental variability. We studied benthic foraminifera in sediment samples collected from 3 m below mean sea level in the Gulf of Panamá and the Gulf of Chiriquí. Temperature loggers deployed from 2016 to 2019 showed that average temperatures were lower and more variable in the Gulf of Panamá due to seasonal upwelling. All sites in both gulfs were dominated by heterotrophic foraminifera, which was likely the result of nutrient enrichment due to upwelling, combined with ENSO effects. However, the Gulf of Chiriquí was characterized by higher abundances of symbiont-bearing foraminifera than the Gulf of Panamá. The orders Miliolida and Rotaliida dominated the foraminiferal assemblages in both gulfs, with Quinqueloculina and Rosalina being the most abundant genera in the two orders, respectively. Miliolids were less abundant in the Gulf of Panamá than in the Gulf of Chiriquí, whereas rotaliid densities were not significantly different between the two gulfs. Lower pH in the Gulf of Panamá as a result of upwelling may have contributed to the lower abundance of miliolids, which secrete tests of high-magnesium calcite. Geochemical analysis of tests of the symbiont-bearing miliolid Sorites marginalis revealed that foraminiferal Mg/Ca ratios were lower in the Gulf of Panamá than in the Gulf of Chiriquí. The offset in foraminiferal Mg/Ca is consistent with the lower mean annual temperature observed in the Gulf of Panamá due to stronger seasonal upwelling. Because the geochemistry and assemblages of foraminifera reflect differences in environmental conditions, they could potentially be used in tandem with coral proxies to reconstruct past environmental change and project the future of coral-reef systems within the ETP.

","language":"English","publisher":"Geological Society of America","doi":"10.2113/gsjfr.50.3.279","usgsCitation":"Zamora-Duran, A.M., Aronson, R.B., Leichter, J., Flannery, J.A., Richey, J.N., and Toth, L., 2020, Imprint of regional oceanography on foraminifera of eastern Pacific Coral Reefs: Journal of Foraminiferal Research, v. 3, no. 50, p. 279-290, https://doi.org/10.2113/gsjfr.50.3.279.","productDescription":"12 p.","startPage":"279","endPage":"290","ipdsId":"IP-111532","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":387181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Panama","otherGeospatial":"Gulf of Chiriqui, Gulf of Panama","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.25439453125,\n 8.51583556120223\n ],\n [\n -83.4521484375,\n 6.68643125265198\n ],\n [\n -78.837890625,\n 6.118707747190845\n ],\n [\n -77.3876953125,\n 5.900188795584184\n ],\n [\n -77.18994140625,\n 8.885071663468993\n ],\n [\n -79.69482421875,\n 9.210560107629691\n ],\n [\n -83.25439453125,\n 8.51583556120223\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","issue":"50","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zamora-Duran, Angelica Maria","contributorId":261127,"corporation":false,"usgs":false,"family":"Zamora-Duran","given":"Angelica","email":"","middleInitial":"Maria","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":819280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aronson, Richard B. 0000-0003-0383-3844","orcid":"https://orcid.org/0000-0003-0383-3844","contributorId":212695,"corporation":false,"usgs":false,"family":"Aronson","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":819281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leichter, James J.","contributorId":261128,"corporation":false,"usgs":false,"family":"Leichter","given":"James J.","affiliations":[{"id":52738,"text":"SCRIPPS INSTITUTION OF OCEANOGRAPHY, UNIVERSITY OF CALIFORNIA AT SAN DIEGO","active":true,"usgs":false}],"preferred":false,"id":819282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flannery, Jennifer A. 0000-0002-1692-2662 jflannery@usgs.gov","orcid":"https://orcid.org/0000-0002-1692-2662","contributorId":4317,"corporation":false,"usgs":true,"family":"Flannery","given":"Jennifer","email":"jflannery@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":819283,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richey, Julie N. 0000-0002-2319-7980 jrichey@usgs.gov","orcid":"https://orcid.org/0000-0002-2319-7980","contributorId":174046,"corporation":false,"usgs":true,"family":"Richey","given":"Julie","email":"jrichey@usgs.gov","middleInitial":"N.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":819284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":819285,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70210871,"text":"tm11B11 - 2020 - Elevation-derived hydrography acquisition specifications","interactions":[],"lastModifiedDate":"2020-07-01T21:02:43.408557","indexId":"tm11B11","displayToPublicDate":"2020-07-01T11:58:32","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"11-B11","displayTitle":"Elevation-Derived Hydrography Acquisition Specifications","title":"Elevation-derived hydrography acquisition specifications","docAbstract":"

Hydrographic features derived from U.S. Geological Survey (USGS) 3D Elevation Program data, and collected for use by the USGS, must meet the specifications described in this document. The specifications described herein pertain to the final product delivered to the USGS, not to methods used to derive the hydrographic features. The specifications describe the collection area, spatial reference system, attribute table structure, feature codes and values, delineation of hydrographic features, topology, positional assessment, metadata, and delivery formats. A companion document, Elevation-Derived Hydrography—Representation, Extraction, Attribution, and Delineation Rules, defines the fields, domains, and minimum feature collection requirements for hydrography features derived from elevation data. Hydrographic features collected to this specification will be suitable for using as breaklines to hydroflatten digital elevation models, processing for preconflation of features to the National Hydrography Dataset, and using for hydroenforcement of digital elevation models.

","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: U.S. Geological Survey Standards in Book 11 Collection and Delineation of Spatial Data","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm11B11","usgsCitation":"Terziotti, S., and Archuleta, C.M., 2020, Elevation-Derived Hydrography Acquisition Specifications: U.S. Geological Survey Techniques and Methods, book 11, chap. B11, 74 p., https://doi.org/10.3133/tm11B11.","productDescription":"Report: vii, 74 p.; Companion Report","numberOfPages":"86","onlineOnly":"Y","ipdsId":"IP-111691","costCenters":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"links":[{"id":376021,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/tm11B12","text":"T&M 11–B12","size":"16.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T&M 11–B12","linkHelpText":"— Elevation-Derived Hydrography—Representation, Extraction, Attribution, and Delineation Rules"},{"id":376020,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/11/b11/tm11b11.pdf","text":"Report","size":"13.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T&M 11–B11"},{"id":376019,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/11/b11/coverthb.jpg"}],"contact":"

Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-07-01","noUsgsAuthors":false,"publicationDate":"2020-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Terziotti, Silvia 0000-0003-3559-5844 seterzio@usgs.gov","orcid":"https://orcid.org/0000-0003-3559-5844","contributorId":1613,"corporation":false,"usgs":true,"family":"Terziotti","given":"Silvia","email":"seterzio@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Archuleta, Christy-Ann 0000-0002-4522-8573 carchule@usgs.gov","orcid":"https://orcid.org/0000-0002-4522-8573","contributorId":192597,"corporation":false,"usgs":true,"family":"Archuleta","given":"Christy-Ann","email":"carchule@usgs.gov","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":791890,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210870,"text":"tm11B12 - 2020 - Elevation-derived hydrography—Representation, extraction, attribution, and delineation rules","interactions":[],"lastModifiedDate":"2023-01-03T17:48:25.705869","indexId":"tm11B12","displayToPublicDate":"2020-07-01T11:56:33","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"11-B12","displayTitle":"Elevation-Derived Hydrography—Representation, Extraction, Attribution, and Delineation Rules","title":"Elevation-derived hydrography—Representation, extraction, attribution, and delineation rules","docAbstract":"

With the increasing availability of 3D Elevation Program (3DEP) quality high resolution elevation data across the United States and the pressing need for better integrated elevation and hydrography data, the U.S. Geological Survey is developing guidance to improve the horizontal and vertical alignment of these datasets. The U.S. Geological Survey is providing the Elevation-Derived Hydrography—Acquisition Specifications for the acquisition of elevation-derived hydrography for the United States, and the companion document The Elevation-Derived Hydrography—Representation, Extraction, Attribution, and Delineation (READ) Rules, which describes the parameters for the portrayal of hydrography features as derived from elevation data. The READ Rules provide a definition, example, attribute value list, delineation instructions, representation rules, and data extraction rules for each hydrography feature required to meet the Elevation-Derived Hydrography—Acquisition Specifications.

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U.S. Geological Survey
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Rolla, MO 65401

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